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    AI-Driven Modeling and Statistical Assessment of AgO/ZnO/g-C3N4 Photocatalysts on Wastewater Treatment: Impact of UV-Visible Light
    (Wiley-V C H Verlag Gmbh, 2025) Yoney, Busra; Aras, Omur
    Minimizing the environmental impact of dye-laden wastewater, remains a critical challenge with high economic implications. This study focuses on the development and optimization of g-C3N4-based photocatalysts doped with AgO and ZnO at varying Zn (0%-100%) and Ag (0%-2.5%) loadings. Catalysts were applied at four dosages (0.03-0.12 g/100 mL), and their methylene blue degradation efficiencies were evaluated over time intervals up to 3 h. Photocatalysts were synthesized using both conventional and ultrasound-assisted (US-assisted) co-precipitation methods. The US-assisted synthesis yielded improved morphology and dispersion, as evidenced by SEM-EDS and XRD analyses, and enhanced photocatalytic performance. Experimental data were used to train three AI models; artificial neural network (ANN), support vector regression (SVR), and Random forest (RF). SVR exhibited the highest predictive accuracy (R-2 = 0.9854, RMSE = 0.0401), while ANN and RF also showed strong performance (R-2 approximate to 0.980). Model robustness was validated through residual analysis and statistical tests. To assess the influence of input variables, one-way and multi-factor Type II ANOVA were conducted. Zn and Ag content, catalyst dosage, and reaction time were all statistically significant (p < 0.05), with US treatment and Zn loading having the most dominant effects. Ag's contribution was also significant but more composition-dependent.
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    Sn-MFI and Fe-MFI zeolites for fructose conversion to levulinic and lactic acids by the one-pot method
    (Wiley, 2024) Sobus, Natalia; Krol, Magdalena; Drozdz, Ewa; Piotrowski, Marcin; Yoney, Busra; Kornaus, Kamil; Komarek, Sebastian
    This paper presents the results of the use of MFI zeolite as a catalyst modified with tin and iron. Sn-MFI and Fe-MFI catalysts were obtained by ion exchange under hydrothermal conditions with and without ammonium exchange. Catalytic materials were characterized with the use of analytical techniques such as X-ray diffraction (XRD), Brunauer-Emmett-Teller method (BET), diffuse reflectance spectroscopy in the ultraviolet-visible range (DRS UV-visible), hydrogen temperature programmed reduction (H-2-TPR), or Fourier transform infrared (FTIR) spectroscopy. The one-pot catalytic conversion of fructose was performed at 220 degrees C for 1-5 h. Based on the results, the influence of time and material selection on the products obtained can be seen. Lactic acid (LAC) was obtained with a yield of 68.7% (after 2 h) and levulinic acid (LA) with a yield of 70.9% (after 5 h) with the participation of MFI. In turn, formic acid with a yield of 28.5% (after 5 h) was obtained with the participation of Fe-MFI.